def run_optavc_mpi():
from optavc.mpi4py_iface import mpirun
options_kwargs = {
'template_file_path': "template.dat",
'queue': "shared",
'command': "qchem input.dat output.dat",
'time_limit': "48:00:00", # has no effect
# 'memory' : "10 GB", #calculator uses memory, number of nodes, and numcores to
# distribute resources
'energy_regex': r"CCSD\(T\) total energy[=\s]+(-\d+\.\d+)",
'success_regex': r"beer",
'fail_regex': r"coffee",
'input_name': "input.dat",
'output_name': "output.dat",
# 'readhess' : False,
'mpi': True, # set to true to use mpi, false to not
# 'submitter' : None,
'maxiter': 20,
'findif': {
'points': 3
}, # set to 5 if you want slightly better frequencies
# 'job_array' : True,
'optking': {
'max_force_g_convergence':
1e-7, # tighter than this is not recommended
'rms_force_g_convergence': 1e-7,
}
}
options_obj = Options(**options_kwargs)
mpirun(options_obj)
def run_optavc(jobtype,
options_dict,
restart_iteration=0,
xtpl_restart=None,
sow=True,
path="."):
""" optavc driver meant to unify input
Parameters
----------
jobtype: str
generous with available strings for optimziation / hessian
options_dict: dict
should contain BOTH optavc and psi4 options
restart_iteration: int
corresponds to the iteration we should begin trying to sow gradients for
xtpl_restart: str
should be ['high_corr', 'large_basis', 'med_basis', 'small_basis']
sow: bool
if False optavc will try to reap only
path: str
for Hessian jobs only
"""
options_obj = Options(**options_dict)
if options_obj.xtpl:
tfps = [
TemplateFileProcessor(open(i).read(), options_obj)
for i in options_obj.xtpl_templates
]
tfp = tfps[0]
xtpl_inputs = [i.input_file_object for i in tfps]
else:
template_file_string = open(options_obj.template_file_path).read()
tfp = TemplateFileProcessor(template_file_string, options_obj)
xtpl_inputs = None
input_obj = tfp.input_file_object
molecule = tfp.molecule
if jobtype.upper() in ['OPT', "OPTIMIZATION"]:
opt_obj = optimize.Optimization(options_obj, input_obj, molecule,
xtpl_inputs)
opt_obj.run(restart_iteration, xtpl_restart)
elif jobtype.upper() in ["HESS", "FREQUENCY", "FREQUENCIES", "HESSIAN"]:
if options_obj.xtpl:
hessian.xtpl_hessian(options_obj, molecule, xtpl_inputs, path, sow)
else:
hess_obj = hessian.Hessian(options_obj,
input_obj,
molecule,
path=path)
hess_obj.compute_hessian(sow)
else:
raise ValueError(
"Can only run deriv or optimizations. For gradients see optimize.py to run or add wrapper here"
)
def initialize_optavc(options_dict, molecule=None):
"""Create the three basic objects required for running optavc. Options, InputFile, Molecule """
options_obj = Options(**options_dict)
if options_obj.xtpl:
options_obj.template_file_path = options_obj._xtpl_templates[0][0]
template_file_string = open(options_obj.template_file_path).read()
tfp = TemplateFileProcessor(template_file_string, options_obj)
input_obj = tfp.input_file_object
if not molecule:
molecule = tfp.molecule
return options_obj, input_obj, molecule
'program': "molpro",
'prep_cmd': "module load molpro",
'command':
"molpro -n 8 --nouse-logfile --no-xml-output -o {}/output.dat {}/input.dat",
'time_limit': "08:00:00",
'memory': "4GB",
# 'num_cores' : 1,
'energy_regex': r" ENERGY\(1\)\s+=\s+(-\d+\.\d+)",
'dask': "/global/cscratch1/sd/md38294/scheduler.json",
'success_regex': r" Variable memory released",
'input_name': "input.dat",
'output_name': "output.dat",
'submitter': submitoptavc,
'maxiter': 20,
'findif': {
'points': 3
},
'job_array': True,
'optking': {
'max_force_g_convergence': 1e-7,
'rms_force_g_convergence': 1e-7,
}
}
from optavc.options import Options
options_obj = Options(**options_kwargs)
from optavc.optimize import Optimization
optimization_obj = Optimization(options_obj)
optimization_obj.run()